Voting-based license plate location

This paper introduces a novel framework which uses all kind of features to elect a license region from an image. The proposed method consists of four major parts: image enhancement, the first round of voting to get the candidate blocks, boundary adjustment, and the second round of voting to get the real plate image. Experiments show that the average accuracy of locating license plate is 98.2% under the experiment databases, which were taken from real scene including different orientation variations, daytime and night time.